1) 16S amplicons

1.1) Data overview

The dataset “Taraspina 18S miTags” contains reads from 122 samples of Malaspina. On average, each sample contains 45940 OTUs:

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##     405   20410   33100   45940   68340  148200


Overall reads per sample:

1.2) Normalization


In order to keep as many samples as possible, we rarefy at 16509 reads per sample. By that, we loose 31 samples, and after removing the exluded samples in the 18S dataset (to make them comparable), we end up with a normalized dataset containing 91 samples and 8881 OTUs.


Datasets summary:

dim(tb16_tax) #original dataset
## [1] 9114  128
dim(tb16_tax_occur) #original dataset with occurrence data alone
## [1] 9114  122
dim(tb16_tax_occur_min16509) #dataset without samples with less than 16509 OTUs
## [1] 8881   91
dim(tb16_tax_occur_ss16509_no_cero) #rarefied dataset
## [1]   91 8204

1.3) General community analysis

1.3.1) Richness and evenness (Shannon index)

Most of the samples take Shannon Index values between 2.5 and 3.5:

1.3.2) Richness: OTU number

Lowest number of OTUs per sample:

## [1] 600

Maximum number of OTUs per sample:

## [1] 1655

In most of the samples, we can identify about 1400 OTUs:

1.3.3) Index of evenness

1.3.3.1) Pielou’s index

The Pielou index (constrained between 0 and 1) takes values closer to 1 as the variation of species proportion in a sample increases. Our samples get values around 0.6, meaning that the numerical composition of different OTUs in a sample is not so variable - we might observe certain dominant species.

1.3.4) Abundance Models

Most of the OTUs show very few occurrences, suggesting that we will probably be able to identify a significant ammount of rare otus:

1.3.4.1) Rank-Abundance or Dominance/Diversity Model (“radfit”)

The OTUs abundance distribution fits relativelly close to log-normal model.

1.3.4.2) Preston’s Lognormal Model

According to Preston’s lognormal model fit into species frequencies groups, we’re missing ~262 species:

veiledspec(tb16_tax_occur_ss16509_prestonfit)
## Extrapolated     Observed       Veiled 
##    9143.6079    8881.0000     262.6079


When computing Prestons’ lognormal model fit without pooling data into groups, we miss ~251 species:

## Extrapolated     Observed       Veiled 
##    9132.6917    8881.0000     251.6917

1.3.5) Rarefaction curves of rarefied and non-rarefied datasets

1.3.6) Beta diversity

1.3.6.1) Dissimilarity matrix using Bray-Curtis index:

The Bray-Curtis dissimilarity, constrained between 0 (minimum distance) and 1 (highest dissimilarity) allows us to quantify the differences between samples according to the composition and relative abundance of their OTUs. In our dataset, most of the samples pairs take dissimilarity values between between 2 and 4, meaning that their composition is substantially similar.

1.3.6.2) Hierarchical clustering

The stations seem to form clusters according to geographic localization, but there are no evident clusters separated from the general groups.

(To be done: assign Longhurst provinces information to each station and check if any of the central clusters is meaningful regarding to the samples’ geographical location)

1.3.6.3) Non-metric multidimensional scaling

We can identify a prominent group in the central part of the NMDS plot and a few outliers in the central-high edge of the plot. The stress parameter takes a value below 0.2, suggesting that the plot is acceptable.

## 
## Call:
## monoMDS(dist = tb16_tax_occur_ss16509_no_cero.bray) 
## 
## Non-metric Multidimensional Scaling
## 
## 91 points, dissimilarity 'bray', call 'vegdist(x = tb16_tax_occur_ss16509_no_cero, method = "bray")'
## 
## Dimensions: 2 
## Stress:     0.1440638 
## Stress type 1, weak ties
## Scores scaled to unit root mean square, rotated to principal components
## Stopped after 69 iterations: Stress nearly unchanged (ratio > sratmax)

When implementing a most robut function for computing NMDS plots, the result is quiet the same:

## Run 0 stress 0.1181392 
## Run 1 stress 0.1261599 
## Run 2 stress 0.1440161 
## Run 3 stress 0.1340847 
## Run 4 stress 0.1606356 
## Run 5 stress 0.1181443 
## ... Procrustes: rmse 0.0004856157  max resid 0.003283112 
## ... Similar to previous best
## Run 6 stress 0.1228213 
## Run 7 stress 0.1572189 
## Run 8 stress 0.1646623 
## Run 9 stress 0.1527362 
## Run 10 stress 0.1346715 
## Run 11 stress 0.1545479 
## Run 12 stress 0.1181442 
## ... Procrustes: rmse 0.0004871289  max resid 0.003309532 
## ... Similar to previous best
## Run 13 stress 0.146291 
## Run 14 stress 0.1588475 
## Run 15 stress 0.1228214 
## Run 16 stress 0.145217 
## Run 17 stress 0.1375357 
## Run 18 stress 0.1453191 
## Run 19 stress 0.127459 
## Run 20 stress 0.1374571 
## *** Solution reached
## Warning in ordiplot(x, choices = choices, type = type, display = display, :
## Species scores not available

1.4) Geographical analysis

Communities quickly change their composition across geographical distances:

1.4.1) Mantel correlograms

Mantel statistic is -significantlly- so low, meaning that the correlation between samples dissimilarity and geographical distances is weak.

## 
## Mantel statistic based on Pearson's product-moment correlation 
## 
## Call:
## mantel(xdis = geo_distances_MP_18S, ydis = tb16_tax_occur_ss16509_no_cero.bray) 
## 
## Mantel statistic r: 0.108 
##       Significance: 0.001 
## 
## Upper quantiles of permutations (null model):
##    90%    95%  97.5%    99% 
## 0.0201 0.0283 0.0361 0.0410 
## Permutation: free
## Number of permutations: 999

Correlograms:

MP_18s_ss16509_mantel_correl_by_1000km<-mantel.correlog(tb16_tax_occur_ss16509_no_cero.bray, D.geo=geo_distances_MP_18S, break.pts=seq(0,20000, by=1000))
plot(MP_18s_ss16509_mantel_correl_by_1000km)

MP_18s_ss16509_mantel_correl_by_100km<-mantel.correlog(tb16_tax_occur_ss16509_no_cero.bray, D.geo=geo_distances_MP_18S, break.pts=seq(0,20000, by=100))
plot(MP_18s_ss16509_mantel_correl_by_100km)

1.5) Abundance vs. occurence

OTUs distribution according to their percentage of occurence and relative abundance.
- red line: OTUs that occur in more than 80% of the samples.
- blue line: regionally abundant OTUs (> 0.1%).
- green line: regionally rare (< 0.001%).

Regionally abundant OTUs (relative abundance over 0.1%):

##     otu_names mean_rabund perc_occur SILVA_consensus
## 1       OTU_1 0.272428825  100.00000            <NA>
## 19      OTU_2 0.079407902  100.00000            <NA>
## 32      OTU_3 0.039178097  100.00000            <NA>
## 60      OTU_5 0.019931186   97.80220            <NA>
## 43   OTU_3619 0.017132846  100.00000            <NA>
## 74      OTU_6 0.017088914  100.00000            <NA>
## 90      OTU_8 0.013937120  100.00000            <NA>
## 101     OTU_9 0.010510418  100.00000            <NA>
## 48      OTU_4 0.009750259   87.91209            <NA>
## 84      OTU_7 0.009306279   98.90110            <NA>
## 62     OTU_51 0.007662154  100.00000            <NA>
## 77     OTU_62 0.006754890  100.00000            <NA>
## 8      OTU_14 0.006132519  100.00000            <NA>
## 7      OTU_13 0.005666573  100.00000            <NA>
## 4      OTU_11 0.005386339  100.00000            <NA>
## 42     OTU_36 0.005374358   45.05495            <NA>
## 51     OTU_43 0.005306463   98.90110            <NA>
## 63     OTU_52 0.004996276  100.00000            <NA>
## 21    OTU_203 0.004903086   81.31868            <NA>
## 87     OTU_75 0.004507032   89.01099            <NA>
## 2      OTU_10 0.004259415   95.60440            <NA>
## 10     OTU_16 0.004256752   94.50549            <NA>
## 9      OTU_15 0.003760187  100.00000            <NA>
## 6      OTU_12 0.003436687   97.80220            <NA>
## 75   OTU_6052 0.003297569   85.71429            <NA>
## 5     OTU_112 0.003284922   84.61538            <NA>
## 28     OTU_27 0.003217026   83.51648            <NA>
## 44     OTU_38 0.003142475  100.00000            <NA>
## 40     OTU_35 0.003125168   91.20879            <NA>
## 96   OTU_8518 0.003100540   87.91209            <NA>
## 24     OTU_23 0.003065927   97.80220            <NA>
## 16     OTU_18 0.002984719   97.80220            <NA>
## 83   OTU_6983 0.002900183   84.61538            <NA>
## 33     OTU_30 0.002793015   98.90110            <NA>
## 37     OTU_33 0.002786359   87.91209            <NA>
## 13     OTU_17 0.002757071   97.80220            <NA>
## 18     OTU_19 0.002601312   94.50549            <NA>
## 25     OTU_24 0.002600646   96.70330            <NA>
## 26     OTU_26 0.002582674   97.80220            <NA>
## 39     OTU_34 0.002564702   92.30769            <NA>
## 29   OTU_2754 0.002532751   98.90110            <NA>
## 22     OTU_21 0.002474841   64.83516            <NA>
## 66   OTU_5345 0.002467519   86.81319            <NA>
## 53     OTU_45 0.002409608   91.20879            <NA>
## 72   OTU_5713 0.002185954   89.01099            <NA>
## 97     OTU_86 0.002120721   96.70330            <NA>
## 34    OTU_303 0.002087439   98.90110            <NA>
## 35     OTU_31 0.001960303   91.20879            <NA>
## 89     OTU_77 0.001953646   75.82418            <NA>
## 92   OTU_8015 0.001932346  100.00000            <NA>
## 78   OTU_6249 0.001923693  100.00000            <NA>
## 11   OTU_1666 0.001923027   90.10989            <NA>
## 52     OTU_44 0.001920364   95.60440            <NA>
## 98   OTU_8731 0.001887083   87.91209            <NA>
## 38   OTU_3305 0.001849807   82.41758            <NA>
## 47   OTU_3997 0.001823181   89.01099            <NA>
## 71     OTU_57 0.001821184   98.90110            <NA>
## 20     OTU_20 0.001819853   83.51648            <NA>
## 31     OTU_29 0.001781912   93.40659            <NA>
## 45     OTU_39 0.001772593   74.72527            <NA>
## 30     OTU_28 0.001756618   70.32967            <NA>
## 15    OTU_178 0.001737980   97.80220            <NA>
## 100  OTU_8904 0.001702701  100.00000            <NA>
## 65     OTU_53 0.001675410   69.23077            <NA>
## 55     OTU_47 0.001669419   94.50549            <NA>
## 17    OTU_182 0.001668753   95.60440            <NA>
## 41    OTU_350 0.001605518   97.80220            <NA>
## 12    OTU_167 0.001552932   79.12088            <NA>
## 50     OTU_42 0.001531632   84.61538            <NA>
## 54     OTU_46 0.001512329   84.61538            <NA>
## 56     OTU_48 0.001474387   82.41758            <NA>
## 64   OTU_5214 0.001439774   98.90110            <NA>
## 27    OTU_269 0.001436446   71.42857            <NA>
## 49     OTU_40 0.001391848   85.71429            <NA>
## 95   OTU_8415 0.001376539   98.90110            <NA>
## 102  OTU_9607 0.001349913   96.70330            <NA>
## 94    OTU_836 0.001349247   94.50549            <NA>
## 85     OTU_72 0.001341925   95.60440            <NA>
## 61   OTU_5092 0.001331941   83.51648            <NA>
## 14    OTU_170 0.001272033   85.71429            <NA>
## 3     OTU_101 0.001246739   68.13187            <NA>
## 86     OTU_73 0.001242745   20.87912            <NA>
## 70   OTU_5677 0.001230764   98.90110            <NA>
## 67     OTU_54 0.001208798   93.40659            <NA>
## 58     OTU_49 0.001182172   93.40659            <NA>
## 68     OTU_55 0.001180841   60.43956            <NA>
## 69   OTU_5631 0.001176182   18.68132            <NA>
## 23     OTU_22 0.001172853   87.91209            <NA>
## 76     OTU_61 0.001168194   97.80220            <NA>
## 82     OTU_69 0.001155547   53.84615            <NA>
## 81     OTU_65 0.001151553   73.62637            <NA>
## 93   OTU_8316 0.001150887   87.91209            <NA>
## 80     OTU_63 0.001146228   73.62637            <NA>
## 59    OTU_497 0.001140903   31.86813            <NA>
## 46    OTU_396 0.001136909  100.00000            <NA>
## 36     OTU_32 0.001125593   73.62637            <NA>
## 88   OTU_7628 0.001118937   57.14286            <NA>
## 73     OTU_59 0.001087652   90.10989            <NA>
## 57   OTU_4850 0.001078333   89.01099            <NA>
## 79    OTU_627 0.001042388  100.00000            <NA>
## 91     OTU_80 0.001039726   42.85714            <NA>
## 99     OTU_89 0.001003116   86.81319            <NA>
##                                                                                                                                                SILVA_classif
## 1                              KC002097.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_unidentified_marine_bacterioplankton
## 19                                             KM520635.1.1287_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 32                                                AACY020285848.922.2246_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_marine_metagenome
## 60            KC001782.1.1355_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_unidentified_marine_bacterioplankton
## 43                                                  AACY023868415.1.1427_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_marine_metagenome
## 74                               KC000519.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 90                                    KC002744.1.1344_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 101                                   KC002796.1.1323_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_2_unidentified_marine_bacterioplankton
## 48                           KJ590614.1.1421_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_Sulfitobacter_uncultured_bacterium
## 84            KC001931.1.1353_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_unidentified_marine_bacterioplankton
## 62                                             JX945368.1.1448_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 77                          KF786428.1.1342_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_SAR11_cluster_alpha_proteobacterium
## 8                                         DQ009267.1.1949_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_SAR116_clade_uncultured_marine_bacterium
## 7                               JX945365.1.1423_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_uncultured_bacterium
## 4                     DQ009111.1.2063_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_marine_bacterium
## 42                                    HQ233040.1.1357_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 51                                    KC000418.1.1315_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 63                                    KC002212.1.1315_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 21                               KC002165.1.1315_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 87                                               GU061737.1.1446_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_uncultured_bacterium
## 2                         KJ549180.1.1447_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Erythrobacteraceae_Erythrobacter_uncultured_bacterium
## 10                                           AACY020257759.244.1709_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_SAR116_clade_marine_metagenome
## 9                             EU804112.1.1492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_uncultured_bacterium
## 6                               JN986244.1.1428_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_uncultured_bacterium
## 75                            EU802327.1.1487_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_uncultured_bacterium
## 5                                              EU237289.1.1306_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 28                            EU802512.1.1493_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_bacterium
## 44                            KC001705.1.1365_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_unidentified_marine_bacterioplankton
## 40                            EU804152.1.1492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_bacterium
## 96                               KC002188.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 24                          AACY023498084.1.1233_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_marine_metagenome
## 16              KC001557.1.1292_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_unidentified_marine_bacterioplankton
## 83                             KC001872.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_unidentified_marine_bacterioplankton
## 33                                                    JN986006.1.1452_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_4_uncultured_bacterium
## 37                                     DQ009141.1.1996_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_uncultured_marine_bacterium
## 13               EU237459.1.1302_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodospirillales_Rhodospirillaceae_AEGEAN-169_marine_group_uncultured_bacterium
## 18                        KJ549185.1.1449_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Erythrobacteraceae_Erythrobacter_uncultured_bacterium
## 25                                        EU802705.1.1252_Bacteria_Bacteroidetes_Cytophagia_Cytophagales_Flammeovirgaceae_Marinoscillum_uncultured_bacterium
## 26              KC002130.1.1290_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_uncultured_unidentified_marine_bacterioplankton
## 39            FN433299.1.1479_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_Flavobacteriia_bacterium
## 29                                    HQ233043.1.1357_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 22                     DQ009121.1.1748_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_uncultured_marine_bacterium
## 66                               KC002668.1.1343_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 53                                    KC002674.1.1343_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 72                                             JX945368.1.1448_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 97                                                    JN985994.1.1438_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 34                                                    EU802406.1.1257_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 35                                        AACY020563509.792.2305_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 89             FN433412.1.1496_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_Flavobacteriia_bacterium
## 92                                                    EU804784.1.1433_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 78                                    KC002895.1.1345_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 11                                    AY664087.1.1207_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 52                                                  AQSI01000003.54241.55782_Bacteria_Marinimicrobia__SAR406_clade__Marinimicrobia_bacterium_SCGC_AAA298-D23
## 98          KF786624.1.1388_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_Flavobacteriales_bacterium
## 38                                             JN986032.1.1449_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 47                                             JN986032.1.1449_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 71                                               EU805317.1.1450_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_SAR116_clade_uncultured_bacterium
## 20             KC003455.1.1350_Bacteria_Proteobacteria_Gammaproteobacteria_Alteromonadales_Alteromonadaceae_Alteromonas_unidentified_marine_bacterioplankton
## 31                                              EU804109.1.1485_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_NS9_marine_group_uncultured_bacterium
## 45                     KC000407.1.1363_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_Formosa_unidentified_marine_bacterioplankton
## 30                                    JX105591.1.1377_Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus_uncultured_bacterium
## 15                          JNAU01000004.222174.223638_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_Prochlorococcus_sp._MIT_0601
## 100                                                   EU804476.1.1440_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 65                                       AACY020549891.3846.5359_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 55                                                    JN986342.1.1465_Bacteria_Proteobacteria_Alphaproteobacteria_Rickettsiales_S25-593_uncultured_bacterium
## 17                         DQ396183.1.1451_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Erythrobacteraceae_Erythrobacter_uncultured_organism
## 41                                    KC002791.1.1322_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_unidentified_marine_bacterioplankton
## 12                                  JN166214.1.1446_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_marine_microorganism
## 50                                              EU804751.1.1482_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_NS7_marine_group_uncultured_bacterium
## 54                                             EU803106.1.1287_Bacteria_Proteobacteria_Deltaproteobacteria_SAR324_clade_Marine_group_B__uncultured_bacterium
## 56                                       AACY020562322.3851.5364_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 64                                                    EF572784.1.1439_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 27                      JQ516674.1.1506_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_uncultured_actinobacterium
## 49          KF786431.1.1388_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS2b_marine_group_uncultured_Flavobacteriales_bacterium
## 95                                        GQ346738.1.1322_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_alpha_proteobacterium
## 102                                                   EU804974.1.1439_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 94                                             KM520431.1.1266_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 85                                                         AACY020555764.489.1966_Bacteria_Proteobacteria_Alphaproteobacteria_OCS116_clade_marine_metagenome
## 61                            JX945339.1.1492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_uncultured_bacterium
## 14                               KC002188.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 3                              JX526770.1.1401_Bacteria_Proteobacteria_Gammaproteobacteria_Thiotrichales_Thiotrichaceae_Thiothrix_uncultured_proteobacterium
## 86                        AACY020462030.661.2167_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_marine_metagenome
## 70                                                    KC294824.1.1401_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 67                                       AACY020481938.3418.4929_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_marine_metagenome
## 58                                     DQ009125.1.1942_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_SAR86_clade_uncultured_marine_bacterium
## 68        FQ032819.21712.23225_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS4_marine_group_uncultured_Flavobacteriia_bacterium
## 69                                               JN832945.1.1352_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_uncultured_bacterium
## 23                               JQ032339.1.1400_Bacteria_Proteobacteria_Gammaproteobacteria_Oceanospirillales_Halomonadaceae_Halomonas_uncultured_bacterium
## 76                        AACY020490277.719.2228_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_marine_metagenome
## 82  ATUR01000005.1108.2578_Bacteria_Proteobacteria_Alphaproteobacteria_Sphingomonadales_Sphingomonadaceae_Sphingopyxis_Sphingopyxis_baekryungensis_DSM_16222
## 81                                       DQ009089.1.1878_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_NS9_marine_group_uncultured_marine_bacterium
## 93                               KC002188.1.1314_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Synechococcus_unidentified_marine_bacterioplankton
## 80                      JQ013156.1.1423_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_Ascidiaceihabitans_uncultured_bacterium
## 59             KC811143.18830.20338_Bacteria_Actinobacteria_Acidimicrobiia_Acidimicrobiales_OM1_clade_Candidatus_Actinomarina_Candidatus_Actinomarina_minuta
## 46                                                    KC294823.1.1400_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 36                          HQ622550.1.1449_Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Aurantimonadaceae_Fulvimarina_Rhizobiales_bacterium_8047
## 88                                    HQ233039.1.1357_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_Prochlorococcus_sp
## 73          EU795293.31983.33492_Bacteria_Bacteroidetes_Flavobacteriia_Flavobacteriales_Flavobacteriaceae_NS5_marine_group_uncultured_bacterium_HF0010_31F02
## 57                                             JX945368.1.1448_Bacteria_Cyanobacteria_Cyanobacteria_SubsectionI_FamilyI_Prochlorococcus_uncultured_bacterium
## 79                                                    EU802825.1.1438_Bacteria_Proteobacteria_Alphaproteobacteria_SAR11_clade_Surface_1_uncultured_bacterium
## 91                KC001532.1.1292_Bacteria_Proteobacteria_Alphaproteobacteria_Rhodobacterales_Rhodobacteraceae_Ruegeria_unidentified_marine_bacterioplankton
## 99                                                              JN018663.1.1390_Bacteria_Proteobacteria_Gammaproteobacteria_KI89A_clade_uncultured_bacterium

Number and roportion of regionally abundant OTUs (%):

## [1] 102
## [1] 1.242236


Cosmopolitan OTUs (relative abundance over 0.1% and occurence in more than 80% of samples):

##    otu_names mean_rabund perc_occur SILVA_consensus PhytoREF_consensus
## 1      OTU_1 0.272428825  100.00000            <NA>               <NA>
## 17     OTU_2 0.079407902  100.00000            <NA>               <NA>
## 27     OTU_3 0.039178097  100.00000            <NA>               <NA>
## 36  OTU_3619 0.017132846  100.00000            <NA>               <NA>
## 62     OTU_6 0.017088914  100.00000            <NA>               <NA>
## 72     OTU_8 0.013937120  100.00000            <NA>               <NA>
## 82     OTU_9 0.010510418  100.00000            <NA>               <NA>
## 53    OTU_51 0.007662154  100.00000            <NA>               <NA>
## 65    OTU_62 0.006754890  100.00000            <NA>               <NA>
## 7     OTU_14 0.006132519  100.00000            <NA>               <NA>
## 6     OTU_13 0.005666573  100.00000            <NA>               <NA>
## 3     OTU_11 0.005386339  100.00000            <NA>               <NA>
## 54    OTU_52 0.004996276  100.00000            <NA>               <NA>
## 8     OTU_15 0.003760187  100.00000            <NA>               <NA>
## 37    OTU_38 0.003142475  100.00000            <NA>               <NA>
## 73  OTU_8015 0.001932346  100.00000            <NA>               <NA>
## 66  OTU_6249 0.001923693  100.00000            <NA>               <NA>
## 81  OTU_8904 0.001702701  100.00000            <NA>               <NA>
## 38   OTU_396 0.001136909  100.00000            <NA>               <NA>
## 67   OTU_627 0.001042388  100.00000            <NA>               <NA>
## 69     OTU_7 0.009306279   98.90110            <NA>               <NA>
## 43    OTU_43 0.005306463   98.90110            <NA>               <NA>
## 28    OTU_30 0.002793015   98.90110            <NA>               <NA>
## 25  OTU_2754 0.002532751   98.90110            <NA>               <NA>
## 29   OTU_303 0.002087439   98.90110            <NA>               <NA>
## 59    OTU_57 0.001821184   98.90110            <NA>               <NA>
## 55  OTU_5214 0.001439774   98.90110            <NA>               <NA>
## 76  OTU_8415 0.001376539   98.90110            <NA>               <NA>
## 58  OTU_5677 0.001230764   98.90110            <NA>               <NA>
## 51     OTU_5 0.019931186   97.80220            <NA>               <NA>
## 5     OTU_12 0.003436687   97.80220            <NA>               <NA>
## 21    OTU_23 0.003065927   97.80220            <NA>               <NA>
## 14    OTU_18 0.002984719   97.80220            <NA>               <NA>
## 11    OTU_17 0.002757071   97.80220            <NA>               <NA>
## 23    OTU_26 0.002582674   97.80220            <NA>               <NA>
## 13   OTU_178 0.001737980   97.80220            <NA>               <NA>
## 35   OTU_350 0.001605518   97.80220            <NA>               <NA>
## 64    OTU_61 0.001168194   97.80220            <NA>               <NA>
## 22    OTU_24 0.002600646   96.70330            <NA>               <NA>
## 78    OTU_86 0.002120721   96.70330            <NA>               <NA>
## 83  OTU_9607 0.001349913   96.70330            <NA>               <NA>
## 2     OTU_10 0.004259415   95.60440            <NA>               <NA>
## 44    OTU_44 0.001920364   95.60440            <NA>               <NA>
## 15   OTU_182 0.001668753   95.60440            <NA>               <NA>
## 70    OTU_72 0.001341925   95.60440            <NA>               <NA>
## 9     OTU_16 0.004256752   94.50549            <NA>               <NA>
## 16    OTU_19 0.002601312   94.50549            <NA>               <NA>
## 47    OTU_47 0.001669419   94.50549            <NA>               <NA>
## 75   OTU_836 0.001349247   94.50549            <NA>               <NA>
## 26    OTU_29 0.001781912   93.40659            <NA>               <NA>
## 57    OTU_54 0.001208798   93.40659            <NA>               <NA>
## 50    OTU_49 0.001182172   93.40659            <NA>               <NA>
## 33    OTU_34 0.002564702   92.30769            <NA>               <NA>
## 34    OTU_35 0.003125168   91.20879            <NA>               <NA>
## 45    OTU_45 0.002409608   91.20879            <NA>               <NA>
## 30    OTU_31 0.001960303   91.20879            <NA>               <NA>
## 10  OTU_1666 0.001923027   90.10989            <NA>               <NA>
## 61    OTU_59 0.001087652   90.10989            <NA>               <NA>
## 71    OTU_75 0.004507032   89.01099            <NA>               <NA>
## 60  OTU_5713 0.002185954   89.01099            <NA>               <NA>
## 39  OTU_3997 0.001823181   89.01099            <NA>               <NA>
## 49  OTU_4850 0.001078333   89.01099            <NA>               <NA>
## 40     OTU_4 0.009750259   87.91209            <NA>               <NA>
## 77  OTU_8518 0.003100540   87.91209            <NA>               <NA>
## 31    OTU_33 0.002786359   87.91209            <NA>               <NA>
## 79  OTU_8731 0.001887083   87.91209            <NA>               <NA>
## 20    OTU_22 0.001172853   87.91209            <NA>               <NA>
## 74  OTU_8316 0.001150887   87.91209            <NA>               <NA>
## 56  OTU_5345 0.002467519   86.81319            <NA>               <NA>
## 80    OTU_89 0.001003116   86.81319            <NA>               <NA>
## 63  OTU_6052 0.003297569   85.71429            <NA>               <NA>
## 41    OTU_40 0.001391848   85.71429            <NA>               <NA>
## 12   OTU_170 0.001272033   85.71429            <NA>               <NA>
## 4    OTU_112 0.003284922   84.61538            <NA>               <NA>
## 68  OTU_6983 0.002900183   84.61538            <NA>               <NA>
## 42    OTU_42 0.001531632   84.61538            <NA>               <NA>
## 46    OTU_46 0.001512329   84.61538            <NA>               <NA>
## 24    OTU_27 0.003217026   83.51648            <NA>               <NA>
## 18    OTU_20 0.001819853   83.51648            <NA>               <NA>
## 52  OTU_5092 0.001331941   83.51648            <NA>               <NA>
## 32  OTU_3305 0.001849807   82.41758            <NA>               <NA>
## 48    OTU_48 0.001474387   82.41758            <NA>               <NA>
## 19   OTU_203 0.004903086   81.31868            <NA>               <NA>

Number and proportion (%) of cosmopolitan OTUs:

## [1] 83
## [1] 1.010839

Number and proportion (%) of rare OTUs:

## [1] 4737
## [1] 57.6909

2.6) Taxonomic composition analysis

2.6.1) Normalized data

No. of OTUs and reads of the rearefied dataset:

## [1] 8211
## [1] 1502319

No. of OTUs and reads of phototrophic groups:

## [1] 1829
## [1] 770258

No. of OTUs and reads of non-phototrophic groups:

## [1] 6382
## [1] 732061


PHOTOTROPHS + HETEROTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    140             11                31
## Bolidophyceae                         88              4                45
## Chlorarachniophyceae                  10              2                 7
## Chlorodendrophyceae                    1              1                 1
## Cryptophyceae                         38              5                17
## Cyanobacteria                     751849           1209                91
## Dictyochophyceae                    1317             31                88
## Dinophyceae                          222             15                52
## Eustigmatophyceae                    116              4                37
## Mamiellophyceae                      849             15                25
## Pelagophyceae                        433             19                65
## Prasinophyceae_clade-IX              573             20                74
## Prasinophyceae_clade-VII             280             15                36
## Prymnesiophyceae                    8924            310                91
## Pyramimonadaceae                      28              3                 8
## Rappemonads                           39              7                25
## Trebouxiophyceae                       1              1                 1
## other_Prasinophyceae                  11              2                10
## other_bacteria                    732061           6382                91
## other_plastids                      5339            155                90


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##          100.0000          100.0000          972.5275
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           9.318926e-03     0.13396663         34.065934
## Bolidophyceae               5.857611e-03     0.04871514         49.450549
## Chlorarachniophyceae        6.656376e-04     0.02435757          7.692308
## Chlorodendrophyceae         6.656376e-05     0.01217878          1.098901
## Cryptophyceae               2.529423e-03     0.06089392         18.681319
## Cyanobacteria               5.004590e+01    14.72415053        100.000000
## Dictyochophyceae            8.766447e-02     0.37754232         96.703297
## Dinophyceae                 1.477715e-02     0.18268177         57.142857
## Eustigmatophyceae           7.721396e-03     0.04871514         40.659341
## Mamiellophyceae             5.651263e-02     0.18268177         27.472527
## Pelagophyceae               2.882211e-02     0.23139691         71.428571
## Prasinophyceae_clade-IX     3.814103e-02     0.24357569         81.318681
## Prasinophyceae_clade-VII    1.863785e-02     0.18268177         39.560440
## Prymnesiophyceae            5.940150e-01     3.77542321        100.000000
## Pyramimonadaceae            1.863785e-03     0.03653635          8.791209
## Rappemonads                 2.595987e-03     0.08525149         27.472527
## Trebouxiophyceae            6.656376e-05     0.01217878          1.098901
## other_Prasinophyceae        7.322014e-04     0.02435757         10.989011
## other_bacteria              4.872873e+01    77.72500304        100.000000
## other_plastids              3.553839e-01     1.88771161         98.901099



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


PHOTOTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    140             11                31
## Bolidophyceae                         88              4                45
## Chlorarachniophyceae                  10              2                 7
## Chlorodendrophyceae                    1              1                 1
## Cryptophyceae                         38              5                17
## Cyanobacteria                     751849           1209                91
## Dictyochophyceae                    1317             31                88
## Dinophyceae                          222             15                52
## Eustigmatophyceae                    116              4                37
## Mamiellophyceae                      849             15                25
## Pelagophyceae                        433             19                65
## Prasinophyceae_clade-IX              573             20                74
## Prasinophyceae_clade-VII             280             15                36
## Prymnesiophyceae                    8924            310                91
## Pyramimonadaceae                      28              3                 8
## Rappemonads                           39              7                25
## Trebouxiophyceae                       1              1                 1
## other_Prasinophyceae                  11              2                10
## other_plastids                      5339            155                90


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##          100.0000          100.0000          872.5275
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           1.817573e-02     0.60142154         34.065934
## Bolidophyceae               1.142474e-02     0.21869874         49.450549
## Chlorarachniophyceae        1.298266e-03     0.10934937          7.692308
## Chlorodendrophyceae         1.298266e-04     0.05467469          1.098901
## Cryptophyceae               4.933412e-03     0.27337343         18.681319
## Cyanobacteria               9.761002e+01    66.10169492        100.000000
## Dictyochophyceae            1.709817e-01     1.69491525         96.703297
## Dinophyceae                 2.882151e-02     0.82012028         57.142857
## Eustigmatophyceae           1.505989e-02     0.21869874         40.659341
## Mamiellophyceae             1.102228e-01     0.82012028         27.472527
## Pelagophyceae               5.621493e-02     1.03881903         71.428571
## Prasinophyceae_clade-IX     7.439066e-02     1.09349371         81.318681
## Prasinophyceae_clade-VII    3.635146e-02     0.82012028         39.560440
## Prymnesiophyceae            1.158573e+00    16.94915254        100.000000
## Pyramimonadaceae            3.635146e-03     0.16402406          8.791209
## Rappemonads                 5.063239e-03     0.38272280         27.472527
## Trebouxiophyceae            1.298266e-04     0.05467469          1.098901
## other_Prasinophyceae        1.428093e-03     0.10934937         10.989011
## other_plastids              6.931444e-01     8.47457627         98.901099



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


Absolute values of cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus              687619            985
## Synechococcus                 61215            158
## other_cyanobacteria            3015             66

Relative values of Cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus          91.4570612      81.472291
## Synechococcus             8.1419274      13.068652
## Other cyanobacteria       0.4010114       5.459057


PROTISTS

## [1] 621
## [1] 18419
occurrence_counts_phototrophs<-data.table()
nrow(tb16_phototrophs)
## [1] 621
#create a table per group and count in how many samples they occur. 
Dinophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Dinophyceae"),]
Dinophyceae_tb_occur <- Dinophyceae_tb[,1:91]
Dinophyceae_tb_occur_len<-length(Dinophyceae_tb_occur[,colSums(Dinophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Dinophyceae",samples_per_class=Dinophyceae_tb_occur_len))

Prasinophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "other_Prasinophyceae"),]
Prasinophyceae_tb_occur <- Prasinophyceae_tb[,1:91]
Prasinophyceae_tb_occur_len<-length(Prasinophyceae_tb_occur[,colSums(Prasinophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="other_Prasinophyceae",samples_per_class=Prasinophyceae_tb_occur_len))

Chrysophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chrysophyceae"),]
Chrysophyceae_tb_occur <- Chrysophyceae_tb[,1:91]
Chrysophyceae_tb_occur_len<-length(Chrysophyceae_tb_occur[,colSums(Chrysophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chrysophyceae",samples_per_class=Chrysophyceae_tb_occur_len))

Pelagophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pelagophyceae"),]
Pelagophyceae_tb_occur <- Pelagophyceae_tb[,1:91]
Pelagophyceae_tb_occur_len<-length(Pelagophyceae_tb_occur[,colSums(Pelagophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pelagophyceae",samples_per_class=Pelagophyceae_tb_occur_len))

Dictyochophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Dictyochophyceae"),]
Dictyochophyceae_tb_occur <- Dictyochophyceae_tb[,1:91]
Dictyochophyceae_tb_occur_len<-length(Dictyochophyceae_tb_occur[,colSums(Dictyochophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Dictyochophyceae",samples_per_class=Dictyochophyceae_tb_occur_len))

Cryptophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Cryptophyceae"),]
Cryptophyceae_tb_occur <- Cryptophyceae_tb[,1:91]
Cryptophyceae_tb_occur_len<-length(Cryptophyceae_tb_occur[,colSums(Cryptophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Cryptophyceae",samples_per_class=Cryptophyceae_tb_occur_len))

Bacillariophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Bacillariophyceae"),]
Bacillariophyceae_tb_occur <- Bacillariophyceae_tb[,1:91]
Bacillariophyceae_tb_occur_len<-length(Bacillariophyceae_tb_occur[,colSums(Bacillariophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Bacillariophyceae",samples_per_class=Bacillariophyceae_tb_occur_len))

Chlorarachniophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chlorarachniophyceae"),]
Chlorarachniophyceae_tb_occur <- Chlorarachniophyceae_tb[,1:91]
Chlorarachniophyceae_tb_occur_len<-length(Chlorarachniophyceae_tb_occur[,colSums(Chlorarachniophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chlorarachniophyceae",samples_per_class=Chlorarachniophyceae_tb_occur_len))

Bolidophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Bolidophyceae"),]
Bolidophyceae_tb_occur <- Bolidophyceae_tb[,1:91]
Bolidophyceae_tb_occur_len<-length(Bolidophyceae_tb_occur[,colSums(Bolidophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Bolidophyceae",samples_per_class=Bolidophyceae_tb_occur_len))

Pinguiophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pinguiophyceae"),]
Pinguiophyceae_tb_occur <- Pinguiophyceae_tb[,1:91]
Pinguiophyceae_tb_occur_len<-length(Pinguiophyceae_tb_occur[,colSums(Pinguiophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pinguiophyceae",samples_per_class=Pinguiophyceae_tb_occur_len))

Prymnesiophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Prymnesiophyceae"),]
Prymnesiophyceae_tb_occur <- Prymnesiophyceae_tb[,1:91]
Prymnesiophyceae_tb_occur_len<-length(Prymnesiophyceae_tb_occur[,colSums(Prymnesiophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Prymnesiophyceae",samples_per_class=Prymnesiophyceae_tb_occur_len))

Mamiellophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Mamiellophyceae"),]
Mamiellophyceae_tb_occur <- Mamiellophyceae_tb[,1:91]
Mamiellophyceae_tb_occur_len<-length(Mamiellophyceae_tb_occur[,colSums(Mamiellophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Mamiellophyceae",samples_per_class=Mamiellophyceae_tb_occur_len))

Eustigmatophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Eustigmatophyceae"),]
Eustigmatophyceae_tb_occur <- Eustigmatophyceae_tb[,1:91]
Eustigmatophyceae_tb_occur_len<-length(Eustigmatophyceae_tb_occur[,colSums(Eustigmatophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Eustigmatophyceae",samples_per_class=Eustigmatophyceae_tb_occur_len))

Chlorophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chlorophyceae"),]
Chlorophyceae_tb_occur <- Chlorophyceae_tb[,1:91]
Chlorophyceae_tb_occur_len<-length(Chlorophyceae_tb_occur[,colSums(Chlorophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chlorophyceae",samples_per_class=Chlorophyceae_tb_occur_len))

Ulvophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Ulvophyceae"),]
Ulvophyceae_tb_occur <- Ulvophyceae_tb[,1:91]
Ulvophyceae_tb_occur_len<-length(Ulvophyceae_tb_occur[,colSums(Ulvophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Ulvophyceae",samples_per_class=Ulvophyceae_tb_occur_len))

Raphydophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Raphydophyceae"),]
Raphydophyceae_tb_occur <- Raphydophyceae_tb[,1:91]
Raphydophyceae_tb_occur_len<-length(Raphydophyceae_tb_occur[,colSums(Raphydophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Raphydophyceae",samples_per_class=Raphydophyceae_tb_occur_len))

Trebouxiophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Trebouxiophyceae"),]
Trebouxiophyceae_tb_occur <- Trebouxiophyceae_tb[,1:91]
Trebouxiophyceae_tb_occur_len<-length(Trebouxiophyceae_tb_occur[,colSums(Trebouxiophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Trebouxiophyceae",samples_per_class=Trebouxiophyceae_tb_occur_len))

Phaeophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Phaeophyceae"),]
Phaeophyceae_tb_occur <- Phaeophyceae_tb[,1:91]
Phaeophyceae_tb_occur_len<-length(Phaeophyceae_tb_occur[,colSums(Phaeophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Phaeophyceae",samples_per_class=Phaeophyceae_tb_occur_len))

Phaeothamniophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Phaeothamniophyceae"),]
Phaeothamniophyceae_tb_occur <- Phaeothamniophyceae_tb[,1:91]
Phaeothamniophyceae_tb_occur_len<-length(Phaeothamniophyceae_tb_occur[,colSums(Phaeothamniophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Phaeothamniophyceae",samples_per_class=Phaeothamniophyceae_tb_occur_len))

Xanthophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Xanthophyceae"),]
Xanthophyceae_tb_occur <- Xanthophyceae_tb[,1:91]
Xanthophyceae_tb_occur_len<-length(Xanthophyceae_tb_occur[,colSums(Xanthophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Xanthophyceae",samples_per_class=Xanthophyceae_tb_occur_len))

Chlorodendrophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Chlorodendrophyceae"),]
Chlorodendrophyceae_tb_occur <- Chlorodendrophyceae_tb[,1:91]
Chlorodendrophyceae_tb_occur_len<-length(Chlorodendrophyceae_tb_occur[,colSums(Chlorodendrophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Chlorodendrophyceae",samples_per_class=Chlorodendrophyceae_tb_occur_len))

IncertaeSedis_Archaeplastida_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "IncertaeSedis_Archaeplastida"),]
IncertaeSedis_Archaeplastida_tb_occur <- IncertaeSedis_Archaeplastida_tb[,1:91]
IncertaeSedis_Archaeplastida_tb_occur_len<-length(IncertaeSedis_Archaeplastida_tb_occur[,colSums(IncertaeSedis_Archaeplastida_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="IncertaeSedis_Archaeplastida",samples_per_class=IncertaeSedis_Archaeplastida_tb_occur_len))

Nephroselmidophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Nephroselmidophyceae"),]
Nephroselmidophyceae_tb_occur <- Nephroselmidophyceae_tb[,1:91]
Nephroselmidophyceae_tb_occur_len<-length(Nephroselmidophyceae_tb_occur[,colSums(Nephroselmidophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Nephroselmidophyceae",samples_per_class=Nephroselmidophyceae_tb_occur_len))

Pavlovophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pavlovophyceae"),]
Pavlovophyceae_tb_occur <- Pavlovophyceae_tb[,1:91]
Pavlovophyceae_tb_occur_len<-length(Pavlovophyceae_tb_occur[,colSums(Pavlovophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pavlovophyceae",samples_per_class=Pavlovophyceae_tb_occur_len))

Rhodophyceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Rhodophyceae"),]
Rhodophyceae_tb_occur <- Rhodophyceae_tb[,1:91]
Rhodophyceae_tb_occur_len<-length(Rhodophyceae_tb_occur[,colSums(Rhodophyceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Rhodophyceae",samples_per_class=Rhodophyceae_tb_occur_len))

Rappemonads_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Rappemonads"),]
Rappemonads_tb_occur <- Rappemonads_tb[,1:91]
Rappemonads_tb_occur_len<-length(Rappemonads_tb_occur[,colSums(Rappemonads_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Rappemonads",samples_per_class=Rappemonads_tb_occur_len))

MOCH_1_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "MOCH_1"),]
MOCH_1_tb_occur <- MOCH_1_tb[,1:91]
MOCH_1_tb_occur_len<-length(MOCH_1_tb_occur[,colSums(MOCH_1_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="MOCH_1",samples_per_class=MOCH_1_tb_occur_len))

MOCH_2_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "MOCH_2"),]
MOCH_2_tb_occur <- MOCH_2_tb[,1:91]
MOCH_2_tb_occur_len<-length(MOCH_2_tb_occur[,colSums(MOCH_2_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="MOCH_2",samples_per_class=MOCH_2_tb_occur_len))

MOCH_5_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "MOCH_5"),]
MOCH_5_tb_occur <- MOCH_5_tb[,1:91]
MOCH_5_tb_occur_len<-length(MOCH_5_tb_occur[,colSums(MOCH_5_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="MOCH_5",samples_per_class=MOCH_5_tb_occur_len))

Prasinophyceae_clade_VII_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Prasinophyceae_clade-VII"),]
Prasinophyceae_clade_VII_tb_occur <- Prasinophyceae_clade_VII_tb[,1:91]
Prasinophyceae_clade_VII_tb_occur_len<-length(Prasinophyceae_clade_VII_tb_occur[,colSums(Prasinophyceae_clade_VII_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Prasinophyceae_clade-VII",samples_per_class=Prasinophyceae_clade_VII_tb_occur_len))

Prasinophyceae_clade_IX_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Prasinophyceae_clade-IX"),]
Prasinophyceae_clade_IX_tb_occur <- Prasinophyceae_clade_IX_tb[,1:91]
Prasinophyceae_clade_IX_tb_occur_len<-length(Prasinophyceae_clade_IX_tb_occur[,colSums(Prasinophyceae_clade_IX_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Prasinophyceae_clade-IX",samples_per_class=Prasinophyceae_clade_IX_tb_occur_len))

Pyramimonadaceae_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "Pyramimonadaceae"),]
Pyramimonadaceae_tb_occur <- Pyramimonadaceae_tb[,1:91]
Pyramimonadaceae_tb_occur_len<-length(Pyramimonadaceae_tb_occur[,colSums(Pyramimonadaceae_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="Pyramimonadaceae",samples_per_class=Pyramimonadaceae_tb_occur_len))

other_plastids_tb <- tb16_phototrophs[which(tb16_phototrophs$class_A == "other_plastids"),]
other_plastids_tb_occur <- other_plastids_tb[,1:91]
other_plastids_tb_occur_len<-length(other_plastids_tb_occur[,colSums(other_plastids_tb_occur) > 0])
occurrence_counts_phototrophs<-rbind(occurrence_counts_phototrophs,data.table(group="other_plastids",samples_per_class=other_plastids_tb_occur_len))

occurrence_counts_phototrophs
##                            group samples_per_class
##  1:                  Dinophyceae                 0
##  2:         other_Prasinophyceae                 0
##  3:                Chrysophyceae                 0
##  4:                Pelagophyceae                 0
##  5:             Dictyochophyceae                 0
##  6:                Cryptophyceae                 0
##  7:            Bacillariophyceae                 0
##  8:         Chlorarachniophyceae                 0
##  9:                Bolidophyceae                 0
## 10:               Pinguiophyceae                 0
## 11:             Prymnesiophyceae                 0
## 12:              Mamiellophyceae                 0
## 13:            Eustigmatophyceae                 0
## 14:                Chlorophyceae                 0
## 15:                  Ulvophyceae                 0
## 16:               Raphydophyceae                 0
## 17:             Trebouxiophyceae                 0
## 18:                 Phaeophyceae                 0
## 19:          Phaeothamniophyceae                 0
## 20:                Xanthophyceae                 0
## 21:          Chlorodendrophyceae                 0
## 22: IncertaeSedis_Archaeplastida                 0
## 23:         Nephroselmidophyceae                 0
## 24:               Pavlovophyceae                 0
## 25:                 Rhodophyceae                 0
## 26:                  Rappemonads                 0
## 27:                       MOCH_1                 0
## 28:                       MOCH_2                 0
## 29:                       MOCH_5                 0
## 30:     Prasinophyceae_clade-VII                 0
## 31:      Prasinophyceae_clade-IX                 0
## 32:             Pyramimonadaceae                 0
## 33:               other_plastids                90
##                            group samples_per_class
#row.names(occurrence_counts_phototrophs)<-occurrence_counts_phototrophs$group
occurrence_counts_phototrophs<-as.data.frame(occurrence_counts_phototrophs)

Absolute values

##                reads_per_class OTUs_per_class samples_per_class
##                          13113            470                NA
## other_plastids            5306            151                90


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##               100               100                NA
##                reads_per_class OTUs_per_class samples_per_class
##                       71.19279       75.68438                NA
## other_plastids        28.80721       24.31562           98.9011



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


2.6.2) Non-rarefied data

No. of OTUs and reads of the rearefied dataset:

## [1] 8881
## [1] 4745946

No. of OTUs and reads of phototrophic groups:

## [1] 1952
## [1] 2504586

No. of OTUs and reads of non-phototrophic groups:

## [1] 6929
## [1] 2241360


PHOTOTROPHS + HETEROTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    450             14                42
## Bolidophyceae                        271              4                61
## Chlorarachniophyceae                  25              2                16
## Chlorodendrophyceae                    8              1                 5
## Cryptophyceae                        103              6                24
## Cyanobacteria                    2449889           1278                91
## Dictyochophyceae                    4003             31                89
## Dinophyceae                          819             17                73
## Eustigmatophyceae                    369              6                56
## Mamiellophyceae                     1248             16                34
## Pelagophyceae                       1076             19                75
## Prasinophyceae_clade-IX             1785             23                80
## Prasinophyceae_clade-VII             923             16                49
## Prymnesiophyceae                   26832            336                91
## Pyramimonadaceae                      51              3                17
## Rappemonads                          136              7                41
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  27              2                16
## other_bacteria                   2241360           6929                91
## other_plastids                     16569            170                90


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##           100.000           100.000          1145.055
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           9.481777e-03     0.15763991         46.153846
## Bolidophyceae               5.710137e-03     0.04503997         67.032967
## Chlorarachniophyceae        5.267654e-04     0.02251999         17.582418
## Chlorodendrophyceae         1.685649e-04     0.01125999          5.494505
## Cryptophyceae               2.170273e-03     0.06755996         26.373626
## Cyanobacteria               5.162067e+01    14.39027137        100.000000
## Dictyochophyceae            8.434567e-02     0.34905979         97.802198
## Dinophyceae                 1.725683e-02     0.19141989         80.219780
## Eustigmatophyceae           7.775057e-03     0.06755996         61.538462
## Mamiellophyceae             2.629613e-02     0.18015989         37.362637
## Pelagophyceae               2.267198e-02     0.21393987         82.417582
## Prasinophyceae_clade-IX     3.761105e-02     0.25897984         87.912088
## Prasinophyceae_clade-VII    1.944818e-02     0.18015989         53.846154
## Prymnesiophyceae            5.653667e-01     3.78335773        100.000000
## Pyramimonadaceae            1.074601e-03     0.03377998         18.681319
## Rappemonads                 2.865604e-03     0.07881995         45.054945
## Trebouxiophyceae            4.214123e-05     0.01125999          1.098901
## other_Prasinophyceae        5.689066e-04     0.02251999         17.582418
## other_bacteria              4.722683e+01    78.02049319        100.000000
## other_plastids              3.491190e-01     1.91419885         98.901099



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:


PHOTOTROPHS

Absolute values

##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae                    450             14                42
## Bolidophyceae                        271              4                61
## Chlorarachniophyceae                  25              2                16
## Chlorodendrophyceae                    8              1                 5
## Cryptophyceae                        103              6                24
## Cyanobacteria                    2449889           1278                91
## Dictyochophyceae                    4003             31                89
## Dinophyceae                          819             17                73
## Eustigmatophyceae                    369              6                56
## Mamiellophyceae                     1248             16                34
## Pelagophyceae                       1076             19                75
## Prasinophyceae_clade-IX             1785             23                80
## Prasinophyceae_clade-VII             923             16                49
## Prymnesiophyceae                   26832            336                91
## Pyramimonadaceae                      51              3                17
## Rappemonads                          136              7                41
## Trebouxiophyceae                       2              1                 1
## other_Prasinophyceae                  27              2                16
## other_plastids                     16569            170                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##           100.000           100.000          1046.154
##                          reads_per_class OTUs_per_class samples_per_class
## Bacillariophyceae           1.796704e-02     0.71721311         46.153846
## Bolidophyceae               1.082015e-02     0.20491803         67.032967
## Chlorarachniophyceae        9.981690e-04     0.10245902         17.582418
## Chlorodendrophyceae         3.194141e-04     0.05122951          5.494505
## Cryptophyceae               4.112456e-03     0.30737705         26.373626
## Cyanobacteria               9.781613e+01    65.47131148        100.000000
## Dictyochophyceae            1.598268e-01     1.58811475         97.802198
## Dinophyceae                 3.270002e-02     0.87090164         80.219780
## Eustigmatophyceae           1.473297e-02     0.30737705         61.538462
## Mamiellophyceae             4.982859e-02     0.81967213         37.362637
## Pelagophyceae               4.296119e-02     0.97336066         82.417582
## Prasinophyceae_clade-IX     7.126926e-02     1.17827869         87.912088
## Prasinophyceae_clade-VII    3.685240e-02     0.81967213         53.846154
## Prymnesiophyceae            1.071315e+00    17.21311475        100.000000
## Pyramimonadaceae            2.036265e-03     0.15368852         18.681319
## Rappemonads                 5.430039e-03     0.35860656         45.054945
## Trebouxiophyceae            7.985352e-05     0.05122951          1.098901
## other_Prasinophyceae        1.078022e-03     0.10245902         17.582418
## other_plastids              6.615465e-01     8.70901639        100.000000



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr:






Absolute values of cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus             2287847           1036
## Synechococcus                152047            167
## other_cyanobacteria            9995             75

Relative values of Cyanobacteria groups richness and abundance:

##                     reads_per_class OTUs_per_class
## Prochlorococcus          93.3857411      81.064163
## Synechococcus             6.2062812      13.067293
## Other cyanobacteria       0.4079777       5.868545


PROTISTS

## [1] 675
## [1] 54727

Absolute values

##                reads_per_class OTUs_per_class samples_per_class
##                          38247            509                NA
## other_plastids           16480            166                91


Relative values

##   reads_per_class    OTUs_per_class samples_per_class 
##               100               100                NA
##                reads_per_class OTUs_per_class samples_per_class
##                       69.88689       75.40741                NA
## other_plastids        30.11311       24.59259               100



Reads per class vs. OTUs per class:



Reads per class vs. samples in which they occurr: